Improving cancer therapy through molecular
diagnostics
Nestebiopsia ja
solunulkoinen DNA
syövän merkkiaineena
Juha Kononen MD PhD
Conflict of interest statement
❖ Received honoraria for lectures from Amgen, Roche,
AstraZeneca, Celgene, Glaxo-Smith-Kline, Lilly
❖ Participated in international oncology meetings with
support from Roche, Novartis, Amgen, Celgene
❖ Participated in advisory board meetings for Celgene,
GSK, Roche, BMS, Pfizer
Liquid biopsy: topics
• Why:
✴ Need for molecular diagnostics
✴ Importance of follow-up and re-testing
• How:
✴ Methods
✴ Opportunities, requirements, limitations
• Examples
Paradigm: oncogene addiction
❖ Implications: Driver
mutations
❖ “Precision medicine”
❖ Predictive
biomarkers
❖ Tissue is the issue:
quality, availability,
representativity
Need for re-testing: clonal evolution during
treatment
Tumors are heterogeneous
Cells that have growth advantage form bulk of the metastatic lesion
No two cancer cell genomes are
identical
Wang et al., Nature 2014
Driver mutations in single cancer cells (TNBC)Molecular evolution rate.
Mutation frequency is 13x higher in TNBC compared to ER+ cells
Biological systems have evolved to sense and
integrate noisy signals from environment
❖ Feedback-loops
❖ Multiple
homologous growth
factor receptor
families
❖ Parallel signalling
cascades
Cancer evolves.
Surgical biopsies are not always
feasible.
Metastatic lesions are heterogeneous.
How to dynamically monitor which clone
forms the bulk of disease burden?
Liquid biopsy:
Tumor-derived
nucleic acids are
present in blood.
Sources:
circulating
cancer cells,
cell-free DNA
Exosomes in cancer
Liquid biopsy for monitoring clonal selection and
molecular evolution
ddPCR is a sensitive method for analyzing known driver mutations from plasma samples
Measuring molecular residual disease
❖ TAYS/KSSHP adjuvant
study
❖ 80 stage III CRC cases
❖ Liquid biopsy follow up
for 3 years after surgery
2. line
Liquid biopsy may predict tumor progression
Misale S, et al. Nature 2012;486:532‒536
Diaz LA, et al. Nature 2012;486;537‒540
Vilar E, Tabernero J. Nature 2012;486:482‒483
Anti-EGFR treatment
KRAS-mutant ctDNA
Other mutant ctDNA
0 4 8 12 16 20 24
Weeks
ctD
NA
am
ount
SD with imagingRadiological disease
progression
Liquid biopsy
Tumor
Metastasis
0 4 8 12 16 20 24
Implications for treatment: re-challenge
❖ Molecular makeup
of bulk of tumor
may fluctuate
during treatment.
❖ Cancer may be
sensitive for
intermittent
treatment.
Siravegna, G. et al. (2015). Clonal evolution and resistance to EGFR blockade in
the blood of colorectal cancer patients. Nature Medicine, 21(7), 795–801.
RAS-määritysmenetelmien herkkyys
Normanno N, Pinto C, Castiglione F, Bardelli A, et al. (2011) KRAS Mutations Testing in Colorectal Carcinoma Patients in Italy: From Guidelines to External Quality Assessment. PLoS ONE 6(12): e29146. doi:10.1371/journal.pone.0029146
Method Sensitivity, % total DNA
Sanger Sequencing 10-25
PCR / RFLP 10
Pyrosequencing 2-10
NGS 2-10
ARMS/Scorpion probes (Therascreen) 1
BEAMing 0.1-1
COLD-PCR 0.1-1
digital droplet PCR 0.01-0.1
Techniques used at KSSHP: Pyrosequencing, NGS, ARMS/Scorpion probes, e-ICE-COLD-PCR, ddPCR
ddPCR = Droplet Digital PCR
Droplet
digital PCR
• Quantitative
• Sensitive
• Suitable for both
mutation and copy
number analyses
• Can be combined with
other PCR methods
Basic concepts: sample partition
• Reactions performed and analysed in each droplet separately
Creating and reading droplets
• Mixing oil with samples
creates uniform reaction
droplets
• Individual droplets are separated
for oil with samples creates
uniform reaction droplets
• Droplets are transferred
to 96 well plate for PCR
Measuring and quantification
• Fluorescent readings
measured for each
droplet in two channels
• Droplets are assigned
as positive or
negative by
thresholding based
on fluorescence
amplitude.
• Count of positive and
negative droplets and
poisson-based 95 %
confidence intervals
are calculated.
Case example:
• Originally response to first-generation TKI
• Mixed response in control CT and some metastatic
lesions showing progression during treatment.
• Analysis of EGFR mutation status from plasma
• Plasma sample preparation in Pori. Frozen plasma
shipped to Jyväskylä for nucleic acid extraction and
ddPCR analysis
Exon 19 del
• Frequency: approximately 18
%
EGFR
p.E746_A750del
WT
p.E746_A750d
el + WT
T790M mutation
• Frequency of mutation: approximately 5 %
• Heterogeneous tutor burden: both sensitive and resistance mutation detected from plasma
• Interpretation: selection of resistant clone during treatment -> switch to another TKI
Liquid biopsy at KSSHP
• EGFR testing: exon 19 del, L858R, T7980M
• RAS mutation: KRAS and NRAS mutations
• BRAF V600
• PIK3CA
• Her-2 amplification
• EGFR copy number analysis
• Custom assay development for any mutation
Tutkimuspyyntö 8000 P-EGFR-D
EGFR-geenin mutaatiotutkimus, plasma
• 9 ml plasmaa
• EDTA putket, erottelu mahdollisimman pian (<2h)
• Näytteen mukaan erillinen lähete (taustatiedot, kysymyksenasettelu)
• Sairaalan sisältä plasma viiveettä molekyylipatologian laboratorioon
• Ulkopuolelta tulevat näytteet lähetetään pakastettuna ja kuivajäissä
• Menetelmä: DNA-eristys ja alleelispesifinen qPCR tai ddPCR
• Tulkinta: Kirjallinen lausunto
• Aika: n. 2 viikkoa
• Hinta: 430 eur
QC
• The European Society of Pathology(ESP) established an EQA program for
testing biomarker mutations in non-small cell lung carcinoma (NSCLC). This
program aims to ensure optimal accuracy and proficiency in lung cancer
biomarker testing across all countries.
• The practical organization of this European EQA program is done in
collaboration with the members of the ESP Lung EQA scheme steering
committee and the Biomedical Quality Assurance Research Unit of the KU
Leuven, lead by Prof. Dr. E Dequeker. The ESP Lung EQA program works in
close contact with Prof. Dr. H van Krieken, president of the ESP. The scheme
is supported by an educational grant from Pfizer.
• This scheme is in collaboration with UK NEQAS ICC&ISH.
• The ESP EQA schemes are accredited by BELAC conform the ISO 17043
QC results 2016
• Osallistujia eri maista 114 laboratoriota
• 59 laboratoriota (52 %) sai hyväksynnän
• KSSHP: 17,5 / 18 pistettä - kirkkaasti hyväksytty
Drug response and sensitivity testing
New approach to cancer therapy
Living biobanks
Drug sensitivity testing
Genome analysis
Immunophenotypes
Transcription profiling
Tumor
Biopsy
Dissociation
Cell sorting
Monitoring molecular
residual disease with serial liquid
biopsies
Diagnostic histology
Experimental
protocols
Response
evaluation
Predictive and
personalised biomarker
development
Adjust therapy
accordingly
Lung cancer in
a non-smoker
Liquid biopsy
NGS
Standard therapyLiquid biopsy
ddPCR
Acknowledgements
Ismo Jantunen
Teijo Kuopio
Aleksi Isomursu
Laura Lahtinen
Noora Nykänen
Outi Välilehto
Reino Pitkänen
Kaija Vasala
Vesa Kataja
Juha Rantala
Rami MäkeläCaroline Heckman
Henrik Edgren
Samuli Eldfors
Astrid Murumägi
Maija Wolf
Olli Kallioniemi
Kimmo Porkka
Erkki Elonen
Kaisa Lehtomäki
Tapio Salminen
Juhani Sand
Kaisa Sunela
Leena Keskinen
Ismo Strander